Overall Statistics |
Total Trades 0 Average Win 0% Average Loss 0% Compounding Annual Return 0% Drawdown 0% Expectancy 0 Net Profit 0% Sharpe Ratio 0 Probabilistic Sharpe Ratio 0% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0 Beta 0 Annual Standard Deviation 0 Annual Variance 0 Information Ratio 5.406 Tracking Error 0.137 Treynor Ratio 0 Total Fees $0.00 Estimated Strategy Capacity $0 Lowest Capacity Asset |
from clr import AddReference AddReference("System") AddReference("QuantConnect.Algorithm") AddReference("QuantConnect.Common") from System import * from QuantConnect import * from QuantConnect.Algorithm import * from QuantConnect.Indicators import * from QuantConnect.Data.Market import TradeBar ### <summary> ### Using rolling windows for efficient storage of historical data; which automatically clears after a period of time. ### </summary> ### <meta name="tag" content="using data" /> ### <meta name="tag" content="history and warm up" /> ### <meta name="tag" content="history" /> ### <meta name="tag" content="warm up" /> ### <meta name="tag" content="indicators" /> ### <meta name="tag" content="rolling windows" /> class RollingWindowAlgorithm(QCAlgorithm): def Initialize(self): '''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.''' self.SetStartDate(2021,11,20) #Set Start Date self.SetEndDate(datetime.now()) #Set End Date self.SetCash(25000) #Set Strategy Cash # Find more symbols here: http://quantconnect.com/data self.AddEquity("QQQ", Resolution.Minute) # Creates a Rolling Window indicator to keep the 2 TradeBar self.windowqqq = RollingWindow[TradeBar](2) # For other security types, use QuoteBar self.qqqrsi = RelativeStrengthIndex("QQQ", 14) self.qqqMACD = self.MACD("QQQ", 12, 26, 9, MovingAverageType.Exponential) #add tqqqrsisma indicator in a rolling window self.qqqrsisma = IndicatorExtensions.SMA(self.qqqrsi, 14) self.qqqrsisma.Updated += self.qqqrsismaUpdated self.qqqrsismarw = RollingWindow[IndicatorDataPoint](14) # create the 5-minutes data consolidator fiveMinuteConsolidator = TradeBarConsolidator(timedelta(minutes=5)) fiveMinuteConsolidator.DataConsolidated += self.fiveMinuteBarHandler # register the 30-minute consolidated bar data to automatically update the indicator self.RegisterIndicator("QQQ", self.qqqrsi, fiveMinuteConsolidator) self.RegisterIndicator("QQQ", self.qqqMACD, fiveMinuteConsolidator) self.SubscriptionManager.AddConsolidator("QQQ", fiveMinuteConsolidator) #Sets the benchmark, brokerage model and warm up time self.SetBenchmark("QQQ") self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage) self.SetWarmUp(500) def qqqrsismaUpdated(self, sender, updated): '''Adds updated values to rolling window''' self.qqqrsismarw.Add(updated) def OnData(self, data): pass def fiveMinuteBarHandler(self, sender, consolidated): # Wait for windows to be ready. if not (self.qqqrsismarw.IsReady): return if not self.qqqMACD.IsReady: return currqqqrsisma = self.qqqrsismarw[0] # Current SMA had index zero. pastqqqrsisma = self.qqqrsismarw[1] # Previous sma qqqrsislope = currqqqrsisma.Value - pastqqqrsisma.Value qqqMACDline = self.qqqMACD.Current.Value qqqsignalline = self.qqqMACD.Signal.Current.Value qqqMACDHistgram = self.qqqMACD.Histogram.Current.Value self.Log("qqqrsislope: {0}, Histogram {1}, MACD {2}, Signal {3}".format(qqqrsislope, qqqMACDHistgram, qqqMACDline, qqqsignalline))